相关论文: NoSQL Databases

Natural Language Interfaces for Databases (NLIDBs) aim to make database querying accessible by allowing users to ask questions in everyday language rather than using formal SQL queries. Despite significant advancements in translation…

Large-scale storage cluster systems need to manage a vast amount of data locations. A naive data locations management maintains pairs of data ID and nodes storing the data in tables. However, it is not practical when the number of pairs is…

AsterixDB is a new, full-function BDMS (Big Data Management System) with a feature set that distinguishes it from other platforms in today's open source Big Data ecosystem. Its features make it well-suited to applications like web data…

The NVMeVirt paper analyzes the implication of storage performance on database engine performance to promote the tunable performance of NVMeVirt. They perform analysis on two very popular database engines, MariaDB and PostgreSQL. The result…

In modern computing, RDBMS are great to store different types of data. To a developer, one of the major objectives is to provide a very low cost and easy to use solution to an existing problem. While commercial databases are more easy to…

Graph processing has become an important part of multiple areas of computer science, such as machine learning, computational sciences, medical applications, social network analysis, and many others. Numerous graphs such as web or social…

Selectivity estimation refers to the ability of the SQL query optimizer to estimate the size of the results of a predicate in the query. It is the main calculation, based on which the optimizer can select the cheapest plan to execute. While…

This paper introduces the recent work of Nebula Graph, an open-source, distributed, scalable, and native graph database. We present a system design trade-off and a comprehensive overview of Nebula Graph internals, including graph data…

The widespread adoption of NoSQL databases has made digital forensics increasingly difficult as storage formats are diverse and often opaque, and audit logs cannot be assumed trustworthy when privileged insiders, such as DevOps or…

Blockchain has come a long way: a system that was initially proposed specifically for cryptocurrencies is now being adapted and adopted as a general-purpose transactional system. As blockchain evolves into another data management system,…

The rapid adoption of AI-powered applications demands high-performance, scalable, and efficient cloud database solutions, as traditional architectures often struggle with AI-driven workloads requiring real-time data access, vector search,…

Many applications require the immutable and consistent sharing of data across organizational boundaries. Because conventional datastores cannot provide this functionality, blockchains have been proposed as one possible solution. Yet public…

With the wide application of time series databases (TSDBs) in big data fields like cluster monitoring and industrial IoT, there have been developed a number of TSDBs for time series data management. Different TSDBs have test reports…

This paper presents a benchmarking suite designed for the evaluation and comparison of time series databases for high-frequency data, with a focus on financial applications. The proposed suite comprises of four specialized databases:…

Natural language interfaces for NoSQL databases are increasingly vital in the big data era, enabling users to interact with complex, unstructured data without deep technical expertise. However, most recent advancements focus on English,…

MongoDB is a popular general-purpose, document-oriented, distributed NoSQL database. It supports transactions in three different deployments: single-document transactions utilizing the WiredTiger storage engine in a standalone node,…

Linked Data and labelled property graphs (LPG) are two data management approaches with complementary strengths and weaknesses, making their integration beneficial for sharing datasets and supporting software ecosystems. In this paper, we…

In modern databases, transaction processing technology provides ACID (Atomicity, Consistency, Isolation, Durability) features. Consistency refers to the correctness of databases and is a crucial property for many applications, such as…

Modern enterprises rely on data management systems to collect, store, and analyze vast amounts of data related with their operations. Nowadays, clusters and hardware accelerators (e.g., GPUs, TPUs) have become a necessity to scale with the…

In the rapidly evolving landscape of modern data-driven technologies, software relies on large datasets and constant data center operations using various database systems to support computation-intensive tasks. As energy consumption in…